Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "84" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 34 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 34 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460017 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.982492 | 23.069129 | 9.303909 | 12.820079 | 0.938881 | 8.685211 | 5.253890 | 3.875421 | 0.4451 | 0.0424 | 0.3472 | nan | nan |
| 2460016 | RF_maintenance | 100.00% | 76.12% | 100.00% | 0.00% | - | - | 20.071599 | 26.531613 | 13.467522 | 14.027155 | 4.207137 | 6.533456 | 4.606753 | 5.376083 | 0.1885 | 0.0355 | 0.1244 | nan | nan |
| 2460015 | RF_maintenance | 100.00% | 69.10% | 100.00% | 0.00% | - | - | 20.868069 | 27.228321 | 13.811925 | 14.477715 | 4.399056 | 6.914839 | 4.199082 | 4.980668 | 0.2019 | 0.0390 | 0.1356 | nan | nan |
| 2460014 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 1.709408 | 24.436166 | 8.236013 | 11.093976 | 1.830603 | 10.396726 | 6.257538 | 4.570156 | 0.4300 | 0.0411 | 0.3384 | nan | nan |
| 2460013 | RF_maintenance | 100.00% | 71.85% | 100.00% | 0.00% | - | - | 20.501318 | 27.349985 | 13.900407 | 14.478249 | 4.420397 | 6.983071 | 6.025413 | 6.952901 | 0.1936 | 0.0359 | 0.1294 | nan | nan |
| 2460012 | RF_maintenance | 100.00% | 99.95% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | 0.1323 | 0.1000 | 0.0540 | nan | nan |
| 2460011 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460010 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460009 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460008 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460007 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 99.42% | 99.25% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.1951 | 0.1881 | 0.1208 | nan | nan |
| 2459998 | RF_maintenance | 100.00% | 71.93% | 100.00% | 0.00% | - | - | 17.330432 | 22.125863 | 12.032177 | 12.677362 | 6.320798 | 10.132770 | 4.584018 | 4.861463 | 0.1911 | 0.0349 | 0.1268 | nan | nan |
| 2459997 | RF_maintenance | 100.00% | 64.76% | 100.00% | 0.00% | - | - | 18.610397 | 24.294852 | 12.756594 | 13.603336 | 6.006543 | 9.412000 | 8.292698 | 9.016510 | 0.2075 | 0.0376 | 0.1368 | nan | nan |
| 2459996 | RF_maintenance | 100.00% | 56.76% | 100.00% | 0.00% | - | - | 20.108250 | 26.238893 | 15.772642 | 16.543339 | 5.545584 | 9.100726 | 3.178874 | 3.907092 | 0.2133 | 0.0363 | 0.1439 | nan | nan |
| 2459995 | RF_maintenance | 100.00% | 99.73% | 99.78% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | 0.5718 | 0.4735 | 0.3872 | nan | nan |
| 2459994 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459993 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459991 | RF_maintenance | 100.00% | 71.40% | 100.00% | 0.00% | - | - | 23.857874 | 29.016775 | 12.806951 | 13.558946 | 7.656448 | 10.649885 | 2.650913 | 3.036270 | 0.1950 | 0.0357 | 0.1276 | nan | nan |
| 2459990 | RF_maintenance | 100.00% | 72.95% | 100.00% | 0.00% | - | - | 19.501260 | 23.842580 | 12.588242 | 13.221327 | 7.622624 | 10.923671 | 2.785102 | 3.004422 | 0.1912 | 0.0386 | 0.1214 | nan | nan |
| 2459989 | RF_maintenance | 100.00% | 70.66% | 100.00% | 0.00% | - | - | 19.542294 | 24.342922 | 11.218516 | 12.032127 | 6.665722 | 9.156247 | 2.098527 | 2.237608 | 0.1917 | 0.0351 | 0.1206 | nan | nan |
| 2459988 | RF_maintenance | 100.00% | 52.05% | 100.00% | 0.00% | - | - | 23.060635 | 28.582085 | 13.005931 | 13.627155 | 8.968406 | 13.045539 | 2.338612 | 2.554051 | 0.2078 | 0.0329 | 0.1252 | nan | nan |
| 2459987 | RF_maintenance | 100.00% | 69.42% | 100.00% | 0.00% | - | - | 19.230552 | 24.161855 | 12.523174 | 13.343741 | 5.114549 | 7.859349 | 4.577065 | 5.389070 | 0.2067 | 0.0371 | 0.1306 | nan | nan |
| 2459986 | RF_maintenance | 100.00% | 52.48% | 100.00% | 0.00% | - | - | 23.217015 | 29.321253 | 13.714718 | 14.445610 | 7.625678 | 11.111194 | 5.671519 | 10.634502 | 0.2419 | 0.0352 | 0.1496 | nan | nan |
| 2459985 | RF_maintenance | 100.00% | 66.00% | 100.00% | 0.00% | - | - | 21.979760 | 27.280308 | 12.674097 | 13.424402 | 5.784320 | 8.474439 | 4.976752 | 5.616583 | 0.2038 | 0.0361 | 0.1319 | nan | nan |
| 2459984 | RF_maintenance | 100.00% | 53.38% | 100.00% | 0.00% | - | - | 19.947623 | 26.004481 | 13.080919 | 13.871656 | 6.843278 | 11.775939 | 3.343727 | 4.980789 | 0.2345 | 0.0382 | 0.1492 | nan | nan |
| 2459983 | RF_maintenance | 100.00% | 58.45% | 100.00% | 0.00% | - | - | 20.430261 | 25.017614 | 12.645255 | 13.218168 | 7.703423 | 10.996400 | 3.924286 | 7.429729 | 0.2418 | 0.0379 | 0.1509 | nan | nan |
| 2459982 | RF_maintenance | 100.00% | 23.07% | 100.00% | 0.00% | - | - | 10.454571 | 11.755948 | 10.721251 | 11.259500 | 3.693145 | 5.375048 | 1.403239 | 3.298092 | 0.3326 | 0.0360 | 0.2095 | nan | nan |
| 2459981 | RF_maintenance | 100.00% | 72.29% | 100.00% | 0.00% | - | - | 18.683397 | 22.790218 | 13.596567 | 14.150773 | 8.832334 | 12.221606 | 2.931716 | 3.456964 | 0.1948 | 0.0379 | 0.1234 | nan | nan |
| 2459980 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 134.473107 | 31.927775 | 47.996684 | 26.476836 | 74.786589 | 26.366126 | 471.913957 | 172.621449 | 0.0209 | 0.0162 | 0.0030 | nan | nan |
| 2459979 | RF_maintenance | 100.00% | 41.64% | 100.00% | 0.00% | - | - | 176.837058 | 65.200172 | 56.843756 | 31.296281 | 2434.526363 | 59.868625 | 4886.835906 | 807.986881 | 0.2669 | 0.0161 | 0.1416 | nan | nan |
| 2459978 | RF_maintenance | 100.00% | 79.08% | 100.00% | 0.00% | - | - | 19.680623 | 23.526714 | 12.364082 | 13.044872 | 7.922984 | 10.874480 | 3.746792 | 4.245004 | 0.1820 | 0.0338 | 0.1197 | nan | nan |
| 2459977 | RF_maintenance | 100.00% | 87.64% | 100.00% | 0.00% | - | - | 19.461636 | 24.405879 | 12.004260 | 12.746605 | 7.702769 | 11.163865 | 3.017511 | 3.923890 | 0.1804 | 0.0381 | 0.1117 | nan | nan |
| 2459976 | RF_maintenance | 100.00% | 77.35% | 100.00% | 0.00% | - | - | 19.752128 | 23.948967 | 12.721217 | 13.367361 | 7.922206 | 10.766961 | 2.768154 | 3.160612 | 0.1868 | 0.0340 | 0.1201 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 23.069129 | 23.069129 | 0.982492 | 12.820079 | 9.303909 | 8.685211 | 0.938881 | 3.875421 | 5.253890 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 26.531613 | 26.531613 | 20.071599 | 14.027155 | 13.467522 | 6.533456 | 4.207137 | 5.376083 | 4.606753 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 27.228321 | 27.228321 | 20.868069 | 14.477715 | 13.811925 | 6.914839 | 4.399056 | 4.980668 | 4.199082 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 24.436166 | 1.709408 | 24.436166 | 8.236013 | 11.093976 | 1.830603 | 10.396726 | 6.257538 | 4.570156 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 27.349985 | 20.501318 | 27.349985 | 13.900407 | 14.478249 | 4.420397 | 6.983071 | 6.025413 | 6.952901 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 22.125863 | 17.330432 | 22.125863 | 12.032177 | 12.677362 | 6.320798 | 10.132770 | 4.584018 | 4.861463 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 24.294852 | 18.610397 | 24.294852 | 12.756594 | 13.603336 | 6.006543 | 9.412000 | 8.292698 | 9.016510 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 26.238893 | 20.108250 | 26.238893 | 15.772642 | 16.543339 | 5.545584 | 9.100726 | 3.178874 | 3.907092 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 29.016775 | 23.857874 | 29.016775 | 12.806951 | 13.558946 | 7.656448 | 10.649885 | 2.650913 | 3.036270 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 23.842580 | 23.842580 | 19.501260 | 13.221327 | 12.588242 | 10.923671 | 7.622624 | 3.004422 | 2.785102 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 24.342922 | 24.342922 | 19.542294 | 12.032127 | 11.218516 | 9.156247 | 6.665722 | 2.237608 | 2.098527 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 28.582085 | 28.582085 | 23.060635 | 13.627155 | 13.005931 | 13.045539 | 8.968406 | 2.554051 | 2.338612 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 24.161855 | 19.230552 | 24.161855 | 12.523174 | 13.343741 | 5.114549 | 7.859349 | 4.577065 | 5.389070 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 29.321253 | 29.321253 | 23.217015 | 14.445610 | 13.714718 | 11.111194 | 7.625678 | 10.634502 | 5.671519 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 27.280308 | 27.280308 | 21.979760 | 13.424402 | 12.674097 | 8.474439 | 5.784320 | 5.616583 | 4.976752 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 26.004481 | 19.947623 | 26.004481 | 13.080919 | 13.871656 | 6.843278 | 11.775939 | 3.343727 | 4.980789 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 25.017614 | 20.430261 | 25.017614 | 12.645255 | 13.218168 | 7.703423 | 10.996400 | 3.924286 | 7.429729 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 11.755948 | 10.454571 | 11.755948 | 10.721251 | 11.259500 | 3.693145 | 5.375048 | 1.403239 | 3.298092 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 22.790218 | 22.790218 | 18.683397 | 14.150773 | 13.596567 | 12.221606 | 8.832334 | 3.456964 | 2.931716 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Temporal Discontinuties | 471.913957 | 31.927775 | 134.473107 | 26.476836 | 47.996684 | 26.366126 | 74.786589 | 172.621449 | 471.913957 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | ee Temporal Discontinuties | 4886.835906 | 176.837058 | 65.200172 | 56.843756 | 31.296281 | 2434.526363 | 59.868625 | 4886.835906 | 807.986881 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 23.526714 | 23.526714 | 19.680623 | 13.044872 | 12.364082 | 10.874480 | 7.922984 | 4.245004 | 3.746792 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 24.405879 | 19.461636 | 24.405879 | 12.004260 | 12.746605 | 7.702769 | 11.163865 | 3.017511 | 3.923890 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | RF_maintenance | nn Shape | 23.948967 | 23.948967 | 19.752128 | 13.367361 | 12.721217 | 10.766961 | 7.922206 | 3.160612 | 2.768154 |